Tal Arbel
Associate Member, McGill University

My research goals are to develop new probabilistic machine learning frameworks in computer vision and in medical imaging, particularly in the context of neurology and neurosurgery. Recent work has focused on the development of probabilistic graphical models for pathology (lesion, tumour) detection and segmentation in large, multi-center patient images dataset, on automatically identifying imaging biomarkers that predict disease progression in patients as well as potential responders to treatment. I have worked extensively on developing fast and efficient multi-modal image registration techniques for clinical interventions, such as image-guided neurosurgery. Recent research led to new frameworks to learn how cortical folding patterns on the surface of the brain vary over the population.